Literature DB >> 8972250

Symmetry of projection in the quantitative analysis of mammographic images.

J W Byng1, N F Boyd, L Little, G Lockwood, E Fishell, R A Jong, M J Yaffe.   

Abstract

Mammographic parenchymal patterns are among the strongest indicators of the risk of developing breast cancer. Risk evaluation through breast patterns may have an important role in studies of the aetiology of breast cancer and for monitoring changes in the breast in evaluating potential risk-modifying interventions. Typically, patterns are assessed by an experienced radiologist according to Wolfe grade, or on a coarse quantitative scale according to percent density. Parenchymal characterization methods, to overcome variability of classification by human observer, are under investigation. These include image segmentation using semi-automatic thresholding and automatic classification through textural and density measures. An important practical question relates to the extent to which information about mammographic pattern is carried by any one of the four views obtained in a typical examination. Specifically, variations of right-left breast symmetry and variations between the two standard views of each breast were tested. The mammograms of 30 premenopausal women, comprising 90 images [30 each of the right cranial-caudal (RCC), left cranial-caudal (LCC) and right medial-lateral oblique (RMLO)] were evaluated. Parameters included both subjective (radiologist classification and interactive image thresholding) and objective (fractal and skewness indices) quantitative measurements of parenchymal pattern. For the parameters tested, a high degree of correlations was observed for measurements on the RCC, LCC and RMLO views. Pearson correlation coefficients between 0.86-0.96 were found for the comparisons of quantitative parameters. The strong correlations suggest that, in the study and application of mammographic density classification, representative information is provided in a single view.

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Year:  1996        PMID: 8972250     DOI: 10.1097/00008469-199610000-00003

Source DB:  PubMed          Journal:  Eur J Cancer Prev        ISSN: 0959-8278            Impact factor:   2.497


  60 in total

1.  Mammographic density and risk of breast cancer by adiposity: an analysis of four case-control studies.

Authors:  Shannon M Conroy; Christy G Woolcott; Karin R Koga; Celia Byrne; Chisato Nagata; Giske Ursin; Celine M Vachon; Martin J Yaffe; Ian Pagano; Gertraud Maskarinec
Journal:  Int J Cancer       Date:  2011-09-17       Impact factor: 7.396

2.  Methods for assessing and representing mammographic density: an analysis of 4 case-control studies.

Authors:  Christy G Woolcott; Shannon M Conroy; Chisato Nagata; Giske Ursin; Celine M Vachon; Martin J Yaffe; Ian S Pagano; Celia Byrne; Gertraud Maskarinec
Journal:  Am J Epidemiol       Date:  2013-10-11       Impact factor: 4.897

3.  Reproductive factors related to childbearing and mammographic breast density.

Authors:  Lusine Yaghjyan; Graham A Colditz; Bernard Rosner; Kimberly A Bertrand; Rulla M Tamimi
Journal:  Breast Cancer Res Treat       Date:  2016-06-28       Impact factor: 4.872

4.  Associations of aspirin and other anti-inflammatory medications with mammographic breast density and breast cancer risk.

Authors:  Lusine Yaghjyan; Akemi Wijayabahu; A Heather Eliassen; Graham Colditz; Bernard Rosner; Rulla M Tamimi
Journal:  Cancer Causes Control       Date:  2020-05-31       Impact factor: 2.506

5.  Does breast density show difference in patients with estrogen receptor-positive and estrogen receptor-negative breast cancer measured on MRI?

Authors:  J-H Chen; F-T Hsu; H-N Shih; C-C Hsu; D Chang; K Nie; O Nalcioglu; M-Y Su
Journal:  Ann Oncol       Date:  2009-08       Impact factor: 32.976

6.  Comparison of breast density in the contralateral normal breast of patients with invasive and in situ breast cancer measured on MRI.

Authors:  J-H Chen; D Chang; K Nie; F-T Hsu; H-N Shih; C-C Hsu; O Nalcioglu; M-Y Su
Journal:  Ann Oncol       Date:  2009-08       Impact factor: 32.976

7.  Mammographic breast density and risk of breast cancer: masking bias or causality?

Authors:  C H van Gils; J D Otten; A L Verbeek; J H Hendriks
Journal:  Eur J Epidemiol       Date:  1998-06       Impact factor: 8.082

8.  Alcohol consumption across the life course and mammographic density in premenopausal women.

Authors:  Ying Liu; Rulla M Tamimi; Graham A Colditz; Kimberly A Bertrand
Journal:  Breast Cancer Res Treat       Date:  2017-09-26       Impact factor: 4.872

9.  Mammographic density, plasma vitamin D levels and risk of breast cancer in postmenopausal women.

Authors:  Angela K Green; Susan E Hankinson; Elizabeth R Bertone-Johnson; Rulla M Tamimi
Journal:  Int J Cancer       Date:  2010-08-01       Impact factor: 7.396

10.  Alcohol intake over the life course and mammographic density.

Authors:  Julie D Flom; Jennifer S Ferris; Parisa Tehranifar; Mary Beth Terry
Journal:  Breast Cancer Res Treat       Date:  2009-01-29       Impact factor: 4.872

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